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Earth Science Informatics

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17.01.2024 | RESEARCH

Assessment of 30 gridded precipitation datasets over different climates on a country scale

verfasst von: Alireza Araghi, Jan F. Adamowski

Erschienen in: Earth Science Informatics | Ausgabe 2/2024

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Abstract

In many regions of the globe, lack of precipitation data is one of the main factors limiting the undertaking of a wide range of environmental studies. Recent studies have shown that gridded precipitation data were dependable replacements for measured precipitation data. In the current study — the most comprehensive to date over the study area and neighboring regions — 30 gridded precipitation datasets from across Iran were evaluated. To evaluate the accuracy of several available gridded precipitation datasets, measured precipitation data were collected from 40 synoptic weather stations across the country from 2001 to 2013. Various performance metrics such as normalized root mean square error (NRMSE) and Nash–Sutcliffe efficiency (NSE), in addition to the Wilcoxon test, served to evaluate the accuracy of gridded precipitation datasets. The Global Precipitation Climatology Center (GPCC) dataset showed the best accuracy with an overall NRMSE of ~ 37% and a NSE of ~ 0.82, while the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) dataset had the weakest performance with an overall NRMSE of ~ 179% and a NSE of -3.25. Due to the temporal limitations of some gridded datasets, even top-ranked ones, and considering the performance metrics of all evaluated datasets, GPCC, TerraClimate, and the Multi-Source Weighted-Ensemble Precipitation (MSWEP) datasets are preferable sources for monthly precipitation over the study area. More studies are needed to expand the results of the current research over the study area and surrounding zones.

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Titel: Assessment of 30 gridded precipitation datasets over different climates on a country scale
verfasst von: Alireza Araghi
Jan F. Adamowski
Publikationsdatum: 17.01.2024
Verlag: Springer Berlin Heidelberg
Erschienen in: Earth Science Informatics / Ausgabe 2/2024
Print ISSN: 1865-0473
Elektronische ISSN: 1865-0481
DOI: https://doi.org/10.1007/s12145-023-01215-0

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